Machine Learning Engineer Salary in India (2026)

The honest starting point for any ML Engineer salary guide in India: most job postings hide the pay. Of the 803 Machine Learning Engineer roles tracked in the July 2026 jobradar snapshot, salary disclosure was the exception, not the rule. This is the norm across Indian tech hiring, which means any salary figure you read, including on this page, draws from self-reported data on platforms like Glassdoor and levels.fyi, not verified offer letters.

That context matters because self-reported data skews toward people willing to share, often higher earners at well-known companies. Treat any range here as directional guidance, not a guarantee. Industry surveys consistently place ML Engineers among the better-paid technical roles in India, but the gap between a fresher at an IT services firm and a senior at a well-funded product startup is large enough to make averages misleading. The sections below break this down by experience level and city so you can calibrate to your situation.

Since the July 2026 jobradar snapshot did not capture disclosed salary bands (most listings skip this field), the figures below come from publicly reported data on Glassdoor and levels.fyi. Sample sizes on these platforms are limited, so treat the ranges as a starting reference rather than a hard benchmark.

Fresher (0-2 years): Glassdoor commonly cites entry-level ML Engineer salaries in India between 6-15 LPA at IT services companies and early-stage startups. For campus placements at top product companies, publicly reported figures on levels.fyi for premier institute graduates can be higher at well-funded firms.

Mid-level (3-5 years): Industry surveys and Glassdoor data commonly cite mid-level ML Engineers at product-focused companies earning 20-45 LPA in fixed pay, with the range driven by specialisation. Skills in MLOps, LLM fine-tuning, and production model serving are commonly cited as factors that push offers toward the higher end.

Senior (6-10 years): Publicly reported data on levels.fyi places senior ML Engineers at established tech firms in the 40-80 LPA range before equity. At multinational product companies, Glassdoor data commonly cites total compensation, including RSUs, significantly above the fixed component alone.

Staff or Principal (10+ years): At this level, levels.fyi data shows packages that are heavily equity-weighted. Industry surveys commonly cite total compensation at top-tier firms well above 80 LPA, with the fixed base making up a smaller share of overall pay.

Bangalore dominates ML hiring by a wide margin. The July 2026 snapshot shows 165 ML Engineer roles in Bangalore out of 803 total, well ahead of every other city. Delhi comes second with 50 openings, followed by Hyderabad at 27. Mumbai has 15 openings, while Pune and Chennai each have 14.

Bangalore and Hyderabad have a high density of product companies and MNC R&D centres, and Glassdoor data commonly cites higher pay at those employer types compared to services firms. Delhi's openings are more mixed, spanning startups, consulting, and government-adjacent tech projects. If you are open to relocating, Bangalore gives you the most options for ML-specific roles, but company type matters more than city location alone.

Know your number before the conversation starts. Look up publicly reported offers on levels.fyi for your role, experience, and city. This gives you a credible reference point rather than a vague expectation. Your current fixed salary is your floor, not your target.

Separate fixed pay from the total package. Many Indian ML offers bundle variable pay, a joining bonus, or equity to inflate the headline CTC. Ask for the fixed, in-hand monthly amount explicitly, and evaluate equity and variable pay separately before comparing offers.

A competing offer moves the needle more than any argument. The single most reliable lever in Indian tech salary negotiations is a second offer letter. It removes ambiguity about your market rate and gives the hiring company a concrete reason to improve their number.

Negotiate beyond the base if the base is stuck. If the company cannot move on fixed pay, ask about a higher joining bonus, an accelerated equity cliff, or an earlier increment review date. These are often easier for HR to approve than a revised salary band.

Ask about the next appraisal cycle upfront. Some companies have long gaps between increment reviews. Knowing this before you sign helps you decide whether to push harder now or plan your next move after joining.

ML Engineer offers in India typically have several components. Understanding each one helps you compare offers across companies on equal terms.

Fixed salary: The guaranteed annual pay, divided into monthly instalments. This is the most important number to negotiate, since variable and equity components are less predictable.

Variable pay: Usually a percentage of fixed, paid quarterly or annually based on individual and company performance. Industry surveys commonly cite variable components for tech roles at around 10-20% of fixed pay, though this varies by company and seniority level.

Joining bonus: A one-time payment, often given to offset unvested equity or an impending increment you are leaving behind. It is sometimes split across the first year. Always check for a clawback clause in case you exit early.

Equity (ESOPs or RSUs): At startups, you typically get ESOPs with value only on a liquidity event. At larger product companies, RSUs vest on a schedule commonly cited in industry surveys as 4 years with a 1-year cliff. The value depends on the stock price at vesting, not at grant.

PF and gratuity: Both are mandatory by law. Provident Fund contributions reduce your monthly take-home from the gross salary. Gratuity accrues after 5 years of service. Always ask for a CTC breakup that shows the in-hand monthly figure clearly, since the CTC headline can include amounts you never see directly.